The buying process has become an important outcome for firms to adapt to the changes in B2B buying. With an increased focus on delivering new customer experiences, firms are finding themselves with lots of customer data that needs to be analyzed. Prior literature has found that technology such as artificial intelligence could be the next logical step in marketing for analyzing and managing customer data but sees slow adoption. This study examined how artificial intelligence can be used to attract and retain B2B customers in the buying process. Empirical data was collected as a multiple caste study with semistructured interviews from B2B salespeople, sales managers, CEOs, CFOs and administrators. The data were analyzed through a thematic analysis. Participants expressed a strong interest in efforts that could affect the relationship such as better engagement, enhanced user experience and information to better meet the needs. Throughout the buying process, many of these efforts could influence the final decision and is believed to be critical in attracting but also maintaining customer relationships. These results have implications for implementing artificial intelligence at firms since it creates a better understanding of the customers' wants and needs and how to correspond to it digitally. Based on the empirical findings, this study contributes with a model that shows the relation of artificial intelligence, customer data and the buying process.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-79290 |
Date | January 2020 |
Creators | Toutin, Joel |
Publisher | Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle |
Source Sets | DiVA Archive at Upsalla University |
Language | Swedish |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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